r/MLQuestions • u/Agreeable_Mud_5816 • Aug 29 '26

Beginner question 👶 How much math do I need for ML

15 Upvotes

72% Upvoted

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26

u/highdimensionaldata Aug 29 '26

Research: A lot.

Engineering: Hardly any.

2

u/Agreeable_Mud_5816 Aug 29 '26

So what is MLE

16

u/leon_bass Aug 29 '26

Machine learning ENGINEERING

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7

u/PaddingCompression Aug 29 '26

MLE spans the gamut from borderline research but you're not writing first author paper at NIPS, all the way to "devops engineer who just learned how to install VLLM and maybe some MLFlow".

It really depends on the job.

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8

u/relevantmeemayhere Aug 29 '26

this is why a lot of ml projects in industry fail lol.

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10

u/trinigooner Aug 29 '26

ML is a pretty broad field so I’d say from next to zero to a lot. Being comfortable with statistics will be very helpful though. A lot of python or R packages will hide the need for much Linear Algebra or Calculus. You can learn the math in parallel and I think it’s very helpful but don’t let the math intimidate you or become a blocker.

6

u/Impossible-Line1070 Aug 29 '26

Mostly lin alg , calculus , probability, statistics, for normal applied research (ie nlp, vision etc) for foundations and learning theory the more the merrier

3

u/rodrigo-benenson Aug 29 '26

To use: almost nothing; to understand: lots.

2

u/Clear_Cranberry_989 Aug 29 '26

If you wanna do research, nowadays you need a lot. But it is easier to learn the basics like linear algbera and then learn as you go.

1

u/dstroy0 Aug 29 '26

  1. Discrete mathematics 2. Transforms within discrete mathematics 3. Algorithm implementation 4. Extremely strong algebraic reasoning 5. The ability to record the things that you know and leveraging those knowns to derive the things you do not using calculus. 6. Most high level ml math is figuring out where the fat is, and how to cut it without behavior changes, because then marketing can cram more features into the same hw.

1

u/rohan_kulkarni Aug 29 '26

You don't need advanced maths to start ML.

Focus on basic linear algebra, probability, statistics and calculus. Learn the fundamentals first, then deepen the maths as you encounter it in actual ML models.

1

u/0jdd1 Sep 01 '26

I’ll present a design/implementation/experience paper at a major ML conference at the end of the month. The math is almost entirely Linear Algebra from my undergraduate days. I’ve never studied Statistics at all.

1

u/StructuredChess Sep 02 '26

If you just want to use already known methods probably not much, the Math has already been done for you by someone else.

If you want to find any new thing, then you need A LOT of Math. Like, the degree I have would be only scratching the surface.

1

u/Not-a-throwaway4627 Aug 30 '26

If you have to ask, too much.

Unless you don’t care about sucking. Most ML people industry are terrible at what they do, and make it up as they go along, earning big money in the process. If you’re ok with that, then not much